Performance improvements for recognition of optical patterns in images using incremental magnification

ABSTRACT

Incremental magnification is used to decode optical patterns, such a barcodes, in a scene. A first image of a scene is acquired using a first magnification of a camera, wherein the first image comprises a barcode. The barcode cannot be decoded. The magnification of the camera is increased by a predetermined magnification from the first magnification to a second magnification. A second image is acquired of the scene, including the barcode. The barcode is decoded after acquiring the second image.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/396,123, filed Aug. 6, 2021, entitled “Performance Improvements ForRecognition Of Optical Patterns In Images,” which application is acontinuation-in-part of U.S. patent application Ser. No. 17/105,082,filed Nov. 25, 2020, entitled “Performance Improvements For RecognitionOf Optical Patterns In Images,” now U.S. Pat. No. 11,087,105, issuedAug. 10, 2021, which application claims priority to and the benefit ofU.S. Provisional Patent Application No. 63/044,635, filed Jun. 26, 2020,and U.S. Provisional Patent Application No. 63/025,850, filed May 15,2020, the disclosures of which are incorporated by reference for allpurposes. U.S. patent application Ser. No. 17/396,123 is acontinuation-in-part of U.S. patent application Ser. No. 17/186,898,filed Feb. 26, 2021, entitled “Efficient Digital Camera ImageAcquisition And Analysis,” now U.S. Pat. No. 11,290,643, issued Mar. 29,2022, which application claims priority to and the benefit of U.S.Provisional Patent Application No. 63/044,635, filed Jun. 26, 2020, thedisclosures of which are incorporated by reference for all purposes.

BACKGROUND

This disclosure generally relates to decoding optical patterns in ascene or image, and more specifically, and without limitation, todecoding barcodes. Barcodes have traditionally been scanned using aspecialized scanner. For example, a barcode scanner comprising a laseris used to shine light on a barcode, and reflected light from thebarcode is detected and used to decode the barcode. As mobile devices(e.g., smartphones and tablets) with cameras have become more common,mobile devices are being used to decode codes by acquiring an image of acode and using image analysis to decode the code. An example of a methodfor using as smartphone to decode a barcode is provided in U.S. Pat. No.8,596,540, granted on Dec. 3, 2013.

BRIEF SUMMARY

Techniques described herein include systems and corresponding methodsfor the automated analysis of an image for recognition of a pattern. Inparticular, and without limitation, included herein are systems thattransform an image for the purpose of measuring significantcharacteristics of the image. The images analyzed and processed hereinare images that are representative of a “real” scene (such as imagesobtained by a camera, scanner, or image detector), including obtainedimages of places and things, wherein the image represents the actualscene.

Mobile devices having a camera, and being capable of hosting mobileapplications, offer a flexible and scalable solution for optical patterndecoding. Such devices detect and decode an optical pattern appearing ina real scene, rather than a single optical pattern isolated from itsenvironment. Scenes also may include multiple optical patterns to bedistinguished when the scene includes different types of opticalpatterns, different orientations, different arrangements, or manyoptical patterns encoding multiple different types of information.Implementation of scanning applications is not straightforward, andstandard device features, such as auto-focus or auto-exposure features,zoom controls, and multi-core processing, may introduce latency and mayreduce performance of scanning processes. To that end, certainembodiments of the present disclosure are addressed at techniques forimproving performance of scanning processes for decoding opticalpatterns appearing in real scenes.

In some embodiments, a mobile device is used for decoding an opticalpattern in a real scene. A mobile device may include a display, acamera, one or more processors in communication with the camera and withthe display, and one or more memory devices storing instructions. Theinstructions, when executed by the one or more processors, may cause themobile device to disable an automatic focus system of the cameracontrolling a focal position of the camera. The instructions, whenexecuted by the one or more processors, may cause the mobile device todetect an optical pattern in a scene using the camera, the opticalpattern encoding an object identifier. The instructions, when executedby the one or more processors, may cause the mobile device to present avisual indication on the display that the optical pattern is notdecoded. The instructions, when executed by the one or more processors,may cause the mobile device to receive a user action. The instructions,when executed by the one or more processors, may cause the mobile deviceto execute a focus cycle of the camera after receiving the user action.The focus cycle may change the focal position of the camera from a firstfocal position to a second focal position. The second focal position maycorrespond to the optical pattern being in focus in the scene. Theinstructions, when executed by the one or more processors, may cause themobile device to acquire an image of the scene using the camera at thesecond focal position. The instructions, when executed by the one ormore processors, may also cause the mobile device to decode the opticalpattern in the image of the scene, generating the object identifier.

In some embodiments, the user action may be received via the displayafter detecting the optical pattern in the scene. The scene may be afirst scene, wherein the user action may include motion of the mobiledevice, and wherein the instructions, when executed, may further causethe one or more processors to detect a scene change from the first sceneto a second scene. Detecting the scene change may include detectingmotion of the mobile device exceeding a threshold motion, or detectingthe scene change based on motion blur in an image of the scene acquiredby the camera. The image of the scene may be a second image. Detectingthe optical pattern in the scene may include acquiring a first image ofthe scene using the camera wherein the focal position of the camera isat the first focal position, detecting the optical pattern in the firstimage without decoding the optical pattern, and ascertaining that theoptical pattern is not in focus in the first image. Ascertaining thatthe optical pattern is not in focus in the first image may includeascertaining a resolution of the optical pattern in the first image anddetermining that the resolution of the optical pattern in the firstimage is below a minimum resolution for decoding the optical pattern.The optical pattern may be a first optical pattern. The objectidentifier may be a first object identifier. The instructions, whenexecuted, may further cause the one or more processors to detect asecond optical pattern in the first image before receiving the useraction, the second optical pattern encoding a second object identifierand decode the second optical pattern in the first image, generating thesecond object identifier.

In certain embodiments, a method implemented by a computer systemincludes one or more operations of the embodiments and their variations,described above.

In certain embodiments, a computer-readable storage medium storescomputer-executable instructions that, when executed, cause one or moreprocessors of a computer system to perform one or more operations of theembodiments and their variations, described above.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is described in conjunction with the appendedfigures.

FIG. 1 depicts an example technique for automated recognition anddecoding of a pattern in an image containing multiple patterns, inaccordance with some embodiments.

FIG. 2 depicts an example technique for automated recognition anddecoding of a pattern in an image of a real scene containing multiplepatterns, in accordance with some embodiments.

FIG. 3 depicts an example technique for exposure control to facilitatedecoding of a pattern in an image of a real scene, in accordance withsome embodiments.

FIG. 4 depicts an example block flow diagram describing an automaticexposure control algorithm, in accordance with some embodiments.

FIG. 5 depicts an example block flow diagram describing implementing amultiple-exposure algorithm, in accordance with some embodiments.

FIG. 6 depicts an example technique for zoom control to facilitatedecoding of a pattern in an image of a real scene, in accordance withsome embodiments.

FIG. 7 depicts an block flow diagram for manual zoom control tofacilitate decoding of a pattern in an image of a real scene, inaccordance with some embodiments.

FIG. 8 depicts an example block flow diagram describing automatic zoomcontrol to facilitate decoding of a pattern in an image of a real scene,in accordance with some embodiments.

FIG. 9 depicts an example technique for focus control to facilitatedecoding of a pattern in an image of a real scene, in accordance withsome embodiments.

FIG. 10 depicts an example block flow diagram describing manual focuscontrol to facilitate decoding of a pattern in an image of a real scene,in accordance with some embodiments.

FIG. 11 depicts an example block flow diagram describing an automaticfocus control algorithm to facilitate decoding of a pattern in an imageof a real scene, in accordance with some embodiments.

FIG. 12 depicts an example block flow diagram describing multi-coreprocessor threading to facilitate decoding of a pattern in an image of areal scene, in accordance with some embodiments.

FIG. 13 depicts a block diagram of an embodiment of a computer system.

In the appended figures, similar components and/or features may have thesame reference label. Further, various components of the same type maybe distinguished by following the reference label by a dash and a secondlabel that distinguishes among the similar components. If only the firstreference label is used in the specification, the description isapplicable to similar components having the same first reference labelirrespective of the second reference label.

DETAILED DESCRIPTION OF THE FIGURES

The ensuing description provides preferred exemplary embodiment(s) only,and is not intended to limit the scope, applicability, or configurationof the disclosure. Rather, the ensuing description of the preferredexemplary embodiment(s) will provide those skilled in the art with anenabling description for implementing a preferred exemplary embodiment.It is understood that various changes may be made in the function andarrangement of elements without departing from the spirit and scope asset forth in the appended claims.

Generally techniques are described for improving performance of scanningprocesses for detection and decoding optical patterns in images, in thecontext of discrete optical patterns appearing in a real scene includingone or more patterns, objects, and/or people in a real environment. Asan illustrative example, a mobile electronic device, such as asmartphone or tablet, captures and/or receives images taken using acamera of the mobile electronic device. The images include, among otherelements in the field of view of the camera, one or more opticalpatterns, such as barcodes. The mobile electronic device implements oneor more approaches to improve decoding performance for optical patternsthat are detected but cannot be decoded, for example, due to being outof focus, being underexposed or overexposed, or being too small in animage. After applying an approach to improve the performance of scanningthe optical pattern, the optical pattern is decoded. The techniquesdescribed herein may be applied to improve exposure strategies, zoomstrategies, focus strategies, and multi-threading strategies, amongothers. In this way, certain embodiments exhibit improved performance inscanning optical patterns in a real scene, for example, by reducing thelatency of scanning, a number of repeated image acquisitions, and/or thecomputational resources applied to scanning, which can reduce the energydemands of scanning optical patterns to recover encoded information.

The techniques described in the following paragraphs, in reference tothe appended figures, constitute multiple technical improvements ofoptical pattern processing. For example, computation resources may beconserved by triggering focus cycles only after in-focus opticalpatterns have been successfully decoded. As another example, a systemmay capture multiple images of a scene at multiple exposure levels,thereby enable scanning of multiple optical patterns at different lightlevels in the same real scene. Implementing the performance improvementtechniques described herein, alone or in combination, provides apotential for significant improvement of processor utilization and powerconsumption of systems employed in image analysis for optical patternrecognition and decoding in real scenes.

Examples of optical patterns include 1D barcodes, 2D barcodes, numbers,letters, and symbols. As scanning optical patterns is moved to mobiledevices, there exists a need to increase scanning speed, increaseaccuracy, and/or manage processing power. Interpreting an opticalpattern (e.g., scanning for an optical pattern) can be divided into twosteps: detecting and decoding. In the detecting step, a position of anoptical pattern within an image is identified and/or a boundary of theoptical pattern is ascertained. In the decoding step, the opticalpattern is decoded (e.g., to provide a numerical string, a letterstring, or an alphanumerical string). As optical patterns, such asbarcodes and QR codes, are used in many areas (e.g., shipping, retail,warehousing, travel), there exists a need for quicker scanning ofoptical patterns. The following are techniques that can increase thespeed and/or accuracy of scanning for optical patterns. The followingtechniques can be used individually, in combination with each other, orin combination with other techniques.

FIG. 1 depicts an example technique for automated recognition anddecoding of a pattern in an image containing multiple patterns, inaccordance with some embodiments. In FIG. 1 , a system 100 having adisplay 110 presents a camera field of view (FOV) of a real scenecontaining multiple optical patterns 114. When a plurality of images arecaptured by a camera and presented in “real time” (e.g., presented onthe display 110 in a sequential manner following capture, albeitpotentially with some latency introduced by system processes), thedisplay may include an image 112. As illustrated, the plurality ofimages depict a real world scene as viewed through a field of view (FOV)of the camera. The real world scene may include multiple objects 150,patterns, or other elements (e.g., faces, images, colors, etc.) of whichthe optical patterns 114 are only a part. For example, FIG. 1 depicts afirst optical pattern 114-1, and a second optical pattern 114-2, amongother optical patterns 114.

In some embodiments, an image 112 may be captured by a camera and/orprovided via additional or alternative system processes (e.g., from amemory device, a communications connection to an online content network,etc.). The optical patterns 114 are detected and/or recognized in theimage 112. In the context of this disclosure, detection and recognitionof optical patterns may describe different approaches for image analysisof optical patterns. Detection may describe detecting an optical patternin an image by characteristic discrete patterns (e.g., parallel bars orsymbols). Recognition may include additional analysis of the patternthat provides descriptive and/or characteristic information (e.g., anoptical pattern type) specific to the optical pattern, but does notnecessarily include decoding the optical pattern. For example, a barcodemay be detected in an image based on image analysis revealing a regionof the image containing multiple parallel bars. After additionalanalysis, the barcode may be recognized as a UPC code. In someembodiments, detection and recognition are concurrent steps implementedby the same image analysis process, and as such are not distinguishable.In some embodiments, image analysis of optical patterns proceeds fromdetection to decoding, without recognition of the optical pattern. Forexample, in some embodiments, a similar approach can be used to detect apattern of characters and in a second step decode the characters withoptical character recognition (OCR).

Detecting optical patterns 114 permits automatic (e.g., without userinteraction) generation and/or presentation on the display 110 of one ormore graphical elements 122. In some embodiments, the graphical elements122 may include, but are not limited to highlighted regions, boundarylines, bounding boxes, dynamic elements, or other graphical elements,overlaid on the image 112 to emphasize or otherwise indicate thepositions of the optical patterns 114 in the plurality of images. Eachoptical pattern 114 may be presented with one or more graphicalelements, such that the image 112 clearly shows the positions of theoptical patterns 114 as well as other metadata, including but notlimited to pattern category, decoding status, or information encoded bythe optical patterns 114.

The system 100 may identify one or more of the optical patterns 114 fordecoding. As mentioned above, the decoding may be automated,initializing upon detection an optical pattern 114 and successfulimplementation of a decoding routine. Subsequent to detection and/ordecoding, object identifier information, optical pattern status, orother information to facilitate the processing of the optical patterns114 may be included by a graphical element 122 associated with anoptical pattern 114 that is decoded. For example, a first graphicalelement 122-1, associated with the first optical pattern 114-1, may begenerated and/or presented via the display 110 at various stages ofoptical pattern detection and/or decoding. For example, afterrecognition, the first graphical element 122-1 may include informationabout the optical pattern template category or the number of patternsdetected. Following decoding, the first graphical element 122-1 maypresent information specific to the first optical pattern 114-1. Wherean optical pattern 114 is detected, but the decoding is unsuccessful,the system 100 may alter a graphical element 122 to indicate decodingfailure, as well as other information indicative of a source of theerror. As an illustrative example, a second graphical element 122-2 mayindicate that the second optical pattern 144-2 cannot be decoded by thesystem 100, for example, through dynamic graphical elements or textualinformation. For example, the second graphical element 122-2 is a yellowbox surrounding the second optical pattern 114-2 after the secondoptical pattern 114-2 is detected; the second graphical element 122-2 ischanged to a red box if the second optical pattern 114-2 is not decoded,or is changed to a green box if the second optical pattern 114-2 isdecoded.

As described in more detail in reference to FIGS. 3-11 below, varioustechniques may be implemented by the system 100 to improve decoding ofthe optical patterns 114. In some embodiments, the techniques may beinitiated automatically or may be manually triggered. For example, thesecond graphical element 122-2 may indicate that the second opticalpattern 114-2 is underexposed, and may trigger an exposure routine.Additionally or alternatively, the system may trigger an exposureroutine in response to a user action associated with the second opticalpattern 114-2, such as a screen tap on the display 110 in a region ofthe image 112 presenting the second optical pattern 114-2 or the secondgraphical element 122-2.

FIG. 2 depicts an example technique for automated recognition anddecoding of a pattern in an image of a real scene containing multiplepatterns, in accordance with some embodiments. The system 100 mayinclude a camera that captures images of a real scene. As illustrated inFIG. 2 , the real scene may include, but is not limited to a retailenvironment, a storage system, or other environment including multipledifferent types of objects 150 that are identifiable using informationencoded in optical patterns 214. The real scene may include multipleoptical patterns 214 at different positions in the real scene. Throughthe FOV of the camera, therefore, the ability of the system 100 todecode a first optical pattern 214-1 may differ from that for a secondoptical pattern 214-2, and from that for a third optical pattern 214-3,etc. As an illustrative example, environmental factors including, butnot limited to, non-uniform lighting, different shelf depth, or positionof an optical pattern 214 in the real scene, may affect the ability ofthe system 100 to decode the optical pattern.

For example, in an environment lit from above, the first optical pattern214-1 may be more brightly lit than the third optical pattern 214-3,nearer the floor. In this way, differences in lighting may influencewhether the third optical pattern 214-3 is sufficiently exposed in animage to allow the system 100 to decode it, where the image of the realscene is captured with exposure settings metered by the first opticalpattern 214-1. Similarly, the image of the real scene may include someoptical patterns 214 in the foreground and other optical patterns 214 inthe background, as when the system 100 is held by a user of the system100 nearer the first optical pattern 214-1 than the third opticalpattern 214-3 (e.g., at eye level). When the system 100 implementsauto-focus routines, the image of the real scene may therefore includethe first optical pattern 214-1 in focus, and may include the secondoptical pattern 214-2 and/or the third optical pattern 214-3 out offocus, for example, as a result of the camera having a relatively narrowdepth of field.

In some embodiments, graphical elements 222 are presented on the display110 (e.g., as an overlay to image 112 in FIG. 1 ) to indicate an opticalpattern 214 that has been detected, recognized, or decoded. Additionallyor alternatively, the graphical elements 222 may include metadataincluding, but not limited to, a notification of decoding failure,whether the optical pattern has been detected or decoded, or a visualindication of object identifier information encoded by the respectiveoptical pattern 214. For example, in an environment where the firstoptical pattern 214-1 is in focus, an optical pattern 214 at the samedistance from the system 100 as the first optical pattern 214-1 may bedetected and decoded, and may be overlaid by a first graphical element222-1 that indicates the optical pattern 214 has been decoded (e.g., asolid line boundary, a highlighted region, etc.). In contrast, where thesecond optical pattern 214-2, and other optical patterns at the same orsimilar distance from the system 100, is out of focus, a secondgraphical element 222-2 may be presented on the display to indicate thatthe optical patterns 214 at that position are detected, but cannot bedecoded (e.g., a dashed, red boundary). Where the third optical pattern214-3 is further out of focus, such that the third optical pattern 214-3and other optical patterns 214 at a similar position are not detected,the system 100 may leave the image of the real scene as it is withoutgenerating or presenting a graphical element 222 via the display 110overlying the third optical patterns 214-3 at the third position (e.g.,the third optical pattern 214-3 is not detected by the system 100because the third optical pattern 214-3 is too out of focus, and/or theexposure of the image is too dark at the third optical pattern 214-3,for the system to distinguish that the third optical pattern 214-3 is abarcode).

As described in reference to the forthcoming paragraphs, various othertechniques may be implemented, individually or in combination, toimprove the performance of the system 100 in detecting, recognizing, anddecoding the optical patterns 214. These techniques include, but are notlimited to, exposure control techniques, focus control techniques, zoomcontrol techniques, image analysis techniques, resolution controltechniques, or multi-threading techniques. Implementing these techniquesmay improve the operation of the system 100 for decoding opticalpatterns 214 in real scenes including multiple optical patterns underdifferent conditions, for example, by improving speed of operation,reducing redundant imaging routines, targeting optical patterns inimages of the real scenes, and may also reduce the computational demandsof the system 100 by controlling system operation at the micro-processorlevel.

A. Exposure Algorithm

FIG. 3 depicts an example technique for exposure control to facilitatedecoding of a pattern in an image of a real scene, in accordance withsome embodiments. In the illustrative example of the real scene as ashelving environment lit from above, the system 100 may initially meterthe exposure of the camera based on a relatively bright region of theimage. For example, typical auto exposure (“AE”) algorithms balanceISO/gain with exposure times to get visually pleasing images/video.While such approaches are developed for imaging, exposure and ISO/gainbalance is not always optimal for detecting or decoding optical patterns314 in the image of the real scene. For a system that implements atypical AE algorithm, some optical patterns 314 may be overexposed,while other optical patterns 314 may be underexposed. For example afirst optical pattern 314-1 may be underexposed or overexposed when thesystem 100 implements an AE algorithm, where the system 100 is able todetect the first optical pattern 314-1, but is unable to decode thefirst optical pattern 314-1. As illustrated in FIG. 3 , the firstoptical pattern 314-1 is a barcode constructed primarily of parallelvertical bars, and while it is visible in the image presented on thedisplay 110, the individual vertical bars are not distinguishable as aresult of underexposure or overexposure.

Multiple approaches to exposure compensation or improvement may beimplemented by the system 100 to improve the performance of the system100 for optical pattern detection and decoding. In some embodiments, thesystem 100 may present graphical elements 322 to indicate, among otherinformation, whether the images are sufficiently exposed, by overlayingthe graphical elements 322 on the optical patterns 314 anddifferentiating between optical patterns that are successfully decodedand those that are detected, but underexposed or overexposed. Forexample, a first graphical element 322-1 may be presented overlaid onthe first optical pattern 314-1, indicating that it is underexposed.

In some embodiments, a user of the system 100 may interact with thesystem 100 and/or the display 110 of the system, for example, by a useraction 312 in a region of the display 110 corresponding to the positionof the first optical pattern 314-1. The user action 312 may include, butis not limited to, a screen tap on the display, a voice command, or aninteraction through peripheral devices. In response, the system 100 maydisable a part or all of the default AE algorithm and may modify one ormore parameters of the camera to meter on the first optical pattern314-1. For example, where the first graphical element 322-1 indicatesthat the first optical pattern 314-1 is underexposed or overexposed, theuser action 312 on the first graphical element 322-1 may be linked totriggering the exposure control. Accordingly, the system 100 may adjustcamera parameters and capture another image (operation 350) that thesystem 100 is able to decode the first optical pattern 314-1 in. Thesystem 100 may also present user controls for enabling an automaticexposure control algorithm to replace the default AE algorithm, asdescribed in more detail in reference to FIG. 4 . In this way, the useraction 312 may also include interacting with a menu or a controlsequence that may initiate the automatic exposure control algorithm.

FIG. 4 depicts an example block flow diagram describing an automaticexposure control algorithm 400, in accordance with some embodiments. Insome embodiments, the system 100 may implement the automatic exposurecontrol algorithm 400 by default, or it may be initiated when opticalpatterns are detected, but cannot be decoded due to being overexposed orunderexposed. The automatic exposure control algorithm 400 may include,at operation 401, disabling an AE algorithm of the system 100 that maybe provided as a default feature of the system 100. To manage theoperation of the camera with respect to metering exposure of imagescaptured by the camera, disabling the default AE algorithm may include,but is not limited to, implementing processor operations on a hardwareor an application layer of the system 100, for example, such that theautomatic exposure control algorithm 400 replaces the AE algorithm whilethe system 100 is capturing images for detection and decoding of opticalpatterns (e.g., optical patterns 314 of FIG. 3 ). In this way, thecamera may be controlled directly by software implemented by the systemthat may temporarily replace the AE algorithm while the software isoperating.

In some embodiments, the system detects an optical pattern at operation405. As described in more detail in reference to FIGS. 1-2 , the realscene may include multiple optical patterns (e.g., optical patterns 114of FIG. 1 ) for detection and/or decoding. The system may, therefore,implement operation 405 for a given optical pattern in the real scene,but may also detect multiple optical patterns. In this way, while theoperations of the automatic exposure control algorithm 400 areillustrated as being performed in a sequence, one or more of theconstituent operations may be executed in parallel, as an approach toimprove performance. For example, parallelizing detection in operation405 may reduce overall latency of the detection and decoding process.

After detection of the optical pattern at operation 405, the system maytrack the optical pattern at operation 410. Tracking the optical patternmay include image processing techniques such as edge detection, keypointdetection, or other techniques enabling the system to distinguish anoptical pattern that encodes information from other patterns appearingin the real scene, such as decorations or other periodic features.Tracking the optical pattern further enables the system to particularizeoptical patterns appearing in the real scene, and enables the system toimplement additional operations, such as inventory management or scenechange detection.

In some embodiments, the system may attempt to decode the opticalpatterns at operation 411. This approach may improve overall systemperformance by reducing additional operations of the automatic exposurecontrol algorithm 400, in cases where the system is able to decode anoptical pattern in the image already taken. For example, the system maybe able to decode the optical pattern directly, at operation 413, inwhich case the subsequent operations are not pursued. In someembodiments, the system proceeds with the subsequent operations forthose optical patterns that cannot be decoded as well as decoding theoptical patterns at operation 413 that the system is able to decode.

For the detected optical patterns, the system may ascertain the exposurelevel(s) of the optical patterns at operation 415. For embodimentsincluding the optional operation 411, the system may implement theoperation 415 to ascertain whether the optical pattern is underexposedor overexposed. Ascertaining the exposure level may include variousapproaches, such as ascertaining a resolution of the optical pattern,ascertaining a contrast between light and dark portions of the opticalpattern, ascertaining a sharpness of the constituent elements of theoptical pattern, or ascertaining an intensity distribution of theoptical pattern. For example, in an illustrative example of a barcode(e.g., first optical pattern 314-1 of FIG. 1 ), a region of an image ofthe real scene including the barcode may be processed by the system,such that the color map of each pixel or a grouping of pixels isdescribed. In this way, the system may ascertain whether individual barsare distinguishable and the image can be used to decode the code. Assuch, the system may evaluate whether the image is sufficiently exposedto decode the optical pattern at operation 420. The system may executethe operation 420 by comparing an output of the image analysis of theoperation 415 against a threshold value. In some embodiments, thethreshold value may be pre-defined. For example, the system may be ableto detect an optical pattern, and may recognize the optical pattern as aUPC barcode, for which a threshold exposure level may be predefined, asin a lookup table or other dataset. In some embodiments, the system mayproceed to decode optical patterns for which the exposure is sufficientat operation 425, for example, where the system has not alreadyattempted to decode the optical patterns at operation 411 or where someof the optical patterns have been decoded, but others have not.

Image processing techniques that are applied to improve aestheticaspects of images may interfere with optical pattern decoding. Somemobile electronic devices that incorporate cameras employ motioncompensation algorithms, serving to reduce image artifacts by smoothingor blurring slight motion in an image. For example, a motioncompensation feature may correct ghost images introduced by motion ofthe mobile electronic device by filtering or smoothing the image, whichmay negatively affect the exposure of the optical pattern detected atthe operation 405. The motion compensation may be an automaticallyenabled feature in medium or low-light conditions, and may interferewith decoding optical patterns. In this way, the system may check for amotion compensation feature at operation 430, and may disable the motioncompensation feature and reacquire an image at operation 435.

In some cases, as when the optical pattern is overexposed orunderexposed in the image of the real scene, the system may modify oneor more parameters of the camera at operation 440 to adjust the exposureof the optical pattern and acquire a new image at the new exposure. Theoperation 440 may include, but is not limited to, adjusting cameraparameters to generate an image with reduced motion blur and highercontrast in the region of the image containing the optical pattern. Thebalance of motion blur and contrast may inform the approach to modifyingcamera parameters. For example, a higher gain (e.g., film speed/ISOvalue) is preferred over a longer exposure time. In some embodiments,exposure is stopped down as preferable to increasing exposure time. Forexample, many cameras set an exposure for 18% gray as a default value.The system may reset the exposure for the camera at 1, 2, 3, 5, or morestops below exposure for 18% gray. In some embodiments, exposure timecannot be slower than the frame rate, or half the frame rate, of thecamera. In some embodiments, a user interface or an application programinterface provides a motion compensation option, which, when selected,limits shutter speed of the camera to be no slower than 1/30, 1/60,1/125, or 1/250 of a second. In some embodiments, if maximum gain isset, then exposure time can be increased.

FIG. 5 depicts an example block flow diagram describing implementing amultiple-exposure algorithm, in accordance with some embodiments. Asdescribed in more detail in reference to FIG. 2 , above, an image of areal scene may include multiple optical patterns at different exposurelevels, such that some optical patterns are either overexposed orunderexposed. To that end, the system executing the multiple exposurealgorithm 500 may detect the optical patterns at operation 505.Detecting the optical patterns may include the image processingtechniques described above in reference to the operation 405 of FIG. 4 .Once detected, the system may ascertain the exposure level(s) of theoptical patterns at operation 510. As with the techniques described inreference to FIG. 4 , the system may optionally attempt to decode alldetected optical patterns directly, rather than executing the operation510, which may reduce the number of instances of the operation 510 thatare implemented by the system. From the exposure values of the opticalpatterns, the system may determine multiple exposure values, andcorresponding camera parameters, at which the optical patterns detectedat the operation 505 may be successfully decoded, at operation 515. Inthe illustrative example of FIGS. 2-3 , if the camera is metered at thelight level of the top shelf in the real scene, optical patterns on themiddle or bottom shelves may be underexposed. In this way the operation515 may include determining one or more modified exposure levels for thecodes on the middle shelf and/or on the bottom shelf.

In some embodiments, the system switches from a live image or video modeto a still image mode at operation 517. Where live images permitdynamics in the real scene to be captured in real time, and may reducelatency and improve speed in decoding individual optical patterns ormultiple optical patterns in sequence, the system may capture an entirereal scene and decode multiple optical patterns from a single positionby capturing multiple still images at different exposure levels. In theexample of the retail shelf, multiple still images may be acquired bythe system at operation 520, for which the camera parameters aremodified to capture the optical patterns on the top shelf, the middleshelf, and the bottom shelf at a sufficient exposure (e.g., operation350 of FIG. 3 ).

In some embodiments, the operation 520 includes capturing images at fullresolution, as opposed to the typically reduced resolution that isapplied for video frames. Full-resolution still images (e.g., RAW-formatimages) may provide an additional advantage of higher bit depth thanvideo frames. Bit depth refers to the number of bits used to indicatethe color of a single pixel, in a bitmapped image or video framebuffer,or the number of bits used for each color component of a single pixel.Higher bit depth may permit the system to apply image processingtechniques to the images to distinguish between constituent elements ofan optical pattern. For example, in a barcode constructed of parallelbars, an image with higher bit depth may provide more precise color dataand, as such, may permit more accurate decoding of optical patterns.

After capturing the multiple images at the multiple exposure values, thesystem may decode the optical patterns at operation 525. In someembodiments, the system may correlate the optical patterns in each ofthe multiple images to the exposure level determined for each opticalpattern at the operation 510. In this way, the system may attempt todecode only the optical patterns appearing in the appropriate images,which may improve system performance by reducing the overall number ofdecoding operations. Alternatively, the system may generate a compositeimage including the optical patterns and decode the optical patternsappearing in the composite image.

In some embodiments, a mobile device is used for decoding an opticalpattern in a real scene. A mobile device may include a camera, one ormore processors in communication with the camera, and one or more memorydevices storing instructions. The instructions, when executed by the oneor more processors, may cause the mobile device to disable an automaticexposure feature controlling one or more parameters of the camera. Theinstructions, when executed by the one or more processors, may cause themobile device to acquire a first image of a scene using the camera. Theinstructions, when executed by the one or more processors, may cause themobile device to detect an optical pattern in the first image, theoptical pattern encoding an object identifier. The instructions, whenexecuted by the one or more processors, may cause the mobile device toascertain an exposure of the optical pattern in the first image. Theinstructions, when executed by the one or more processors, may cause themobile device to modify at least one parameter of the camera based onthe exposure of the optical pattern. The instructions, when executed bythe one or more processors, may cause the mobile device to acquire asecond image using the modified parameter. The instructions, whenexecuted by the one or more processors, may also cause the mobile deviceto decode the optical pattern in the second image, generating the objectidentifier.

In some embodiments, ascertaining the exposure of the optical patternincludes ascertaining that the optical pattern is overexposed orunderexposed and ascertaining that the one or more processors cannotdecode the optical pattern in the first image based on the opticalpattern being overexposed or underexposed. Ascertaining the exposure ofthe optical pattern may include ascertaining that the optical pattern isunresolved or blurred and ascertaining that the one or more processorscannot decode the optical pattern in the first image based on theoptical pattern being unresolved or blurred. Modifying at least oneparameter of the camera may include determining an exposure level of theoptical pattern using the first image and modifying at least oneparameter of the camera providing the exposure level of the opticalpattern, increasing a brightness, a sharpness, or a contrast of theoptical pattern in the second image. The at least one parameter of thecamera may be or include a gain, a frame rate, an exposure time, or anaperture. Modifying the at least one parameter of the camera may includeincreasing or decreasing the exposure time of the camera. Theinstructions, when executed, may further cause the one or moreprocessors to receive a user action comprising an interaction with adisplay of the mobile device, before disabling the automatic exposuresystem. The optical pattern may be a first optical pattern, the exposuremay be a first exposure, and the modified parameter may be a firstmodified parameter. The instructions, when executed, may further causethe one or more processors to detect a second optical pattern in thefirst image. The instructions, when executed, may further cause the oneor more processors to ascertain a second exposure of the second opticalpattern in the first image. The instructions, when executed, may furthercause the one or more processors to modify at least one of the one ormore parameters of the camera using the second exposure of the secondoptical pattern. The instructions, when executed, may further cause theone or more processors to acquire a third image using the at least onemodified parameter. The instructions, when executed, may also furthercause the one or more processors to decode the second optical pattern inthe third image. The instructions, when executed, may further cause theone or more processors to detect a plurality of optical patterns in thefirst image. The instructions, when executed, may further cause the oneor more processors to determine a plurality of exposure values based onthe plurality of optical patterns in the first image. The instructions,when executed, may further cause the one or more processors to acquire aplurality of images, each image of the plurality of images acquiredaccording to one or parameters of the camera determined using anexposure value of the plurality of the exposure values. Theinstructions, when executed, may also further cause the one or moreprocessors to decode the plurality of optical patterns in the pluralityof images. The instructions, when executed, may further cause the one ormore processors to disable the automatic exposure feature controllingone or more parameters of the camera before acquiring the first image ofthe scene using the camera. The instructions, when executed, may furthercause the one or more processors to track the optical pattern in aplurality of images before acquiring the first image of the scene usingthe camera.

In some embodiments, a mobile device is used for decoding an opticalpattern in a real scene. A mobile device may include a camera, one ormore processors in communication with the camera, and one or more memorydevices storing instructions. The instructions, when executed by the oneor more processors, may cause the mobile device to disable an automaticexposure feature controlling one or more parameters of the camera. Theinstructions, when executed by the one or more processors, may cause themobile device to acquire a first image of a scene using the camera. Theinstructions, when executed by the one or more processors, may cause themobile device to detect an optical pattern in the first image, theoptical pattern encoding an object identifier. The instructions, whenexecuted by the one or more processors, may cause the mobile device toascertain an exposure of the optical pattern in the first image. Theinstructions, when executed by the one or more processors, may cause themobile device to modify at least one parameter of the camera based onthe exposure of the optical pattern. The instructions, when executed bythe one or more processors, may cause the mobile device to acquire asecond image using the modified parameter. The instructions, whenexecuted by the one or more processors, may also cause the mobile deviceto decode the optical pattern in the second image, generating the objectidentifier.

In some embodiments, ascertaining the exposure of the optical patternincludes ascertaining that the optical pattern is overexposed orunderexposed and ascertaining that the one or more processors cannotdecode the optical pattern in the first image based on the opticalpattern being overexposed or underexposed. Ascertaining the exposure ofthe optical pattern may include ascertaining that the optical pattern isunresolved or blurred and ascertaining that the one or more processorscannot decode the optical pattern in the first image based on theoptical pattern being unresolved or blurred. Modifying at least oneparameter of the camera may include determining an exposure level of theoptical pattern using the first image and modifying at least oneparameter of the camera providing the exposure level of the opticalpattern, increasing a brightness, a sharpness, or a contrast of theoptical pattern in the second image. The at least one parameter of thecamera may be or include a gain, a frame rate, an exposure time, or anaperture. Modifying the at least one parameter of the camera may includeincreasing or decreasing the exposure time of the camera. Theinstructions, when executed, may further cause the one or moreprocessors to receive a user action comprising an interaction with adisplay of the mobile device, before disabling the automatic exposuresystem. The optical pattern may be a first optical pattern, the exposuremay be a first exposure, and the modified parameter may be a firstmodified parameter. The instructions, when executed, may further causethe one or more processors to detect a second optical pattern in thefirst image. The instructions, when executed, may further cause the oneor more processors to ascertain a second exposure of the second opticalpattern in the first image. The instructions, when executed, may furthercause the one or more processors to modify at least one of the one ormore parameters of the camera using the second exposure of the secondoptical pattern. The instructions, when executed, may further cause theone or more processors to acquire a third image using the at least onemodified parameter. The instructions, when executed, may also furthercause the one or more processors to decode the second optical pattern inthe third image. The instructions, when executed, may further cause theone or more processors to detect a plurality of optical patterns in thefirst image. The instructions, when executed, may further cause the oneor more processors to determine a plurality of exposure values based onthe plurality of optical patterns in the first image. The instructions,when executed, may further cause the one or more processors to acquire aplurality of images, each image of the plurality of images acquiredaccording to one or parameters of the camera determined using anexposure value of the plurality of the exposure values. Theinstructions, when executed, may also further cause the one or moreprocessors to decode the plurality of optical patterns in the pluralityof images. The instructions, when executed, may further cause the one ormore processors to disable the automatic exposure feature controllingone or more parameters of the camera before acquiring the first image ofthe scene using the camera. The instructions, when executed, may furthercause the one or more processors to track the optical pattern in aplurality of images before acquiring the first image of the scene usingthe camera.

B. Tap to Zoom

FIG. 6 depicts an example technique for zoom control to facilitatedecoding of a pattern in an image of a real scene, in accordance withsome embodiments. In some embodiments, zoom (mechanical and/or digital)can be used to assist in decoding an optical pattern. Using a zoomfeature of a camera can help in various situations, such as helping auser avoid bending over to scan a barcode. For example, an employee at agrocery store uses a mobile device to scan barcodes on store shelves.The mobile device can detect and decode barcodes on shelves that arewaist high to the employee. However, for barcodes on shelves near theemployee's feet and knees, or above the employee's head, the mobiledevice might not be able to decode those barcodes because of lack ofresolution or because the barcodes are too small in the images used todetect and decode. Accordingly, a camera on the mobile device could beused to zoom to a barcode.

As illustrated in FIG. 6 , multiple optical patterns 614 may be includedin the image of the real scene. In some embodiments, the image of thereal scene may be captured by a camera incorporated into a mobileelectronic device that is positioned nearer to a first optical pattern614-1 than a second optical pattern 614-2. In this way, the firstoptical pattern 614-1 may be of sufficient size to be successfullydecoded by the system 600, while the second optical pattern 614-2 may betoo small to be successfully decoded, based, for example, on theresolution, bit-depth, or other parameter of the image of the realscene.

As described in more detail in reference to FIGS. 1-2 , the system 600may generate and/or present graphical elements 622 overlaid on the imageof the real scene at positions corresponding to the optical patterns614. The graphical elements 622 may indicate that the optical patternsare detected, recognized, decoded, or may present other information,such as whether an image limitation is preventing the respective opticalpattern 614 from being decoded (e.g., exposure, focus, size, etc.). Theindication provided by the graphical elements 622 may permit a user ofthe system 600 to identify those optical patterns 614 appearing in theimage that the system is unable to detect and/or decode. In this way,the system 600 may receive a user action 612, such as a screen tap inthe region of an optical pattern 614, which may cause the system toadjust a magnification of the camera (operation 650) to generate amagnified image localized on a region of the image corresponding to theuser action 612. For example, the user of the system 600 may wish todecode the second optical pattern 614-2, when the second optical pattern614-2 is too small in a first image. The user of the system 600 may tapthe display 610 of the system 600 to cause the system to capture asecond image at a higher magnification, such that the second opticalpattern is captured with sufficient size to be decoded. Additionally oralternatively, the system 600 may automatically modify the magnificationsetting and capture images at increased magnification for opticalpatterns that have been detected, but are too small to be decoded, asdescribed in more detail in reference to FIGS. 7-8 , below.

FIG. 7 depicts a block-flow diagram for manual zoom control tofacilitate decoding of a pattern in an image of a real scene, inaccordance with some embodiments. As described in reference to FIG. 6 ,manual zoom control may be implemented to improve performance of opticalpattern detection and decoding in images containing multiple opticalpatterns, where an optical pattern is included in an image of a realscene, but is too small to be detected and/or decoded. A system 700 mayreceive a user action 712 at operation 705. The user action 712 mayinclude a screen tap on a display of the system 700, or other forms ofuser interaction, including through peripherals or voice interaction. Inresponse to receiving the user action 712, the system 700 may increasethe magnification of a camera of the system 700, and may generate animage of the region corresponding to an optical pattern that waspreviously too small to be decoded, at operation 715. In some cases, theuser action 712 indicates the region to be magnified, but the system 700may also identify a region including multiple optical patterns that areeach too small to be decoded, and may magnify that region in a zoomedimage.

The zoom of the camera can be set to a predetermined zoom factor. Forexample, in response to receiving the user action 712, the system 700may increase the magnification by a fixed magnification factor (e.g.,1.5, 2, or 3). In some embodiments, the magnification factor is equal toor greater than 1.5 and/or equal to or less than 3. In this way, thesystem may respond to repeated user actions 712 by incrementing themagnification and capturing an image at operation 720. In someembodiments, the user of the system 100 may provide a second user action714, received by the system 700 at operation 725. The second user actionmay be the same as the user action 712, for example, as a repetition ofthe user action 712 or two instances of the user action 712 in shortsuccession, such that the system 700 recognizes the combination ofactions as the second user action 714.

As illustrated in FIG. 7 , the system 700 may increment themagnification by a fixed increment for each successive user action 712.The fixed increment may be at least 0.1×, at least 0.2×, at least 0.3×,at least 0.4×, at least 0.5×, at least 0.6×, at least 0.7×, at least0.8×, at least 0.9×, at least 1.0×, at least 1.5×, or more. After afirst instance of the user action 712, the system may increase themagnification by a factor of 2, and after a second instance of the useraction 712, the system 700 may increase the magnification by a factor of1.5. After receiving the second user action, the system 700 may returnthe camera to the initial magnification at operation 730. In someembodiments, the system implements a binary quantized zoom. For example,only two levels: 1. “out” and 2. “in” are used, where level 2 is themagnification factor times level 1, and/or level 1 is the widest angleof the camera (however, level 1 “out” could be set to not be the widestangle of the camera based on a specific scanning application).

FIG. 8 depicts an example block flow diagram describing automatic zoomcontrol to facilitate decoding of a pattern in an image of a real scene,in accordance with some embodiments. As opposed to receiving a useraction to trigger magnification, automatic zoom control may improvedetection and decoding of optical patterns in real scenes that includemultiple optical patterns, for example, by identifying optical patentsthat are detected, but are too small to be decoded. As described inreference to FIGS. 6-7 , a system may modify the magnification of acamera between two fixed magnifications, for example by applying amagnification factor, and may capture a zoomed image. In someembodiments, the system may apply a magnification to the camera afterwaiting for a period of time after ascertaining that the optical patternis too small to be decoded. The period of time may be at least 0.1 sec,at least 0.2 sec, at least 0.3 sec, at least 0.4 sec, at least 0.5 sec,at least 0.6 sec, at least 0.7 sec, at least 0.8 sec, at least 0.9 sec,at least 1.0 sec, at least 1.5 sec, at least 2.0 sec, at least 2.5 sec,at least 3.0 sec, or longer. In some embodiments, the system may returnthe camera to an initial magnification after an optical pattern in amagnified region of an image of the real scene is decoded. Automatedzoom features may be accompanied by visual indications and prompts,presented via a display or with speakers, to guide the user of thesystem.

As an illustrative example of automatic zoom implementation, a mobiledevice detects a barcode at operation 805, and ascertains the resolutionof the barcode at operation 810. Where the mobile device ascertains thatthe resolution is not sufficient to decode the barcode at operation 815,the mobile device implements a zoom at operation 820, and acquires animage at the higher magnification. Where the resolution is sufficient,the mobile device decodes the barcode at operation 825, and thenreverses the zoom after decoding the barcode (and/or decodes otherbarcodes detected before reversing zoom). In some embodiments, themobile device may repeat the operation 820 for multiple zoom increments.That being said, where the camera, either by hardware or software, isbounded by an upper magnification limit or is limited to a single zoomincrement, the mobile device may optionally assess whether theadditional zoom increment is permitted at operation 830. Where thecamera is not permitted to zoom further, the mobile device may promptthe user at operation 835 to move the mobile device closer to thebarcode, for example, by an auditory prompt, or by a visual indicationpresented as a graphical element (e.g., graphical element 622 of FIG. 6).

In some embodiments, a mobile device is used for decoding an opticalpattern in a real scene. A mobile device may include a camera, one ormore processors in communication with the camera, and one or more memorydevices storing instructions. The instructions, when executed by the oneor more processors, may cause the mobile device to acquire a first imageof a scene using the camera, wherein a magnification of the camera isset at a first magnification. The instructions, when executed by the oneor more processors, may cause the mobile device to detect an opticalpattern in a region of the first image, the optical pattern encoding anobject identifier. The instructions, when executed by the one or moreprocessors, may cause the mobile device to ascertain that the region ofthe first image is too small to decode the optical pattern. Theinstructions, when executed by the one or more processors, may cause themobile device to change a magnification of the camera from the firstmagnification to a second magnification, after ascertaining that theregion of the first image is too small to decode the optical pattern.The instructions, when executed by the one or more processors, may causethe mobile device to acquire a second image using the camera, whereinmagnification of the camera is set at the second magnification. Theinstructions, when executed by the one or more processors, may alsocause the mobile device to decode the optical pattern in the secondimage, generating the object identifier.

In some embodiments, the mobile device further includes a display.Changing the magnification of the camera may include receiving a useraction via the display and changing the magnification of the camera fromthe first magnification to the second magnification after receiving theuser action. The magnification may be limited to a set of magnificationsincluding the first magnification and the second magnification. Eachmagnification of the set of magnifications may be separated by anincrement of at least 0.5×. The user action may be a first user action.The instructions, when executed, may further cause the one or moreprocessors to receive a second user action via the display and changethe magnification of the camera from the second magnification to a thirdmagnification of the set of magnifications after receiving the seconduser action. The third magnification may be greater than the secondmagnification and the second magnification may be greater than the firstmagnification. The first user action and the second user action may beor include a user screen tap on the display. The instructions, whenexecuted, may further cause the one or more processors to wait for aperiod of time after ascertaining that the region of the first image istoo small to decode the optical pattern before changing themagnification of the camera. The period of time may be at least 1second. The instructions, when executed, may further cause the one ormore processors to change the magnification of the camera from thesecond magnification to the first magnification, after decoding theoptical pattern.

C. Focus Strategies

FIG. 9 depicts an example technique for focus control to facilitatedecoding of a pattern in an image of a real scene, in accordance withsome embodiments. Mobile devices having a camera often use an auto-focusfeature while the camera is operating. The auto-focus (AF) feature isused to trigger a focus of the camera. When a focus of the camera istriggered, the camera implements a focus algorithm to find a sharpimage. For example, the camera can adjust focus from a minimum value toa maximum value and set the focus where a portion of a scene isconsidered sharp (or sharpest). In some cases, the AF feature isoptimized to identify and focus on faces, which may prove ineffectivewhen the mobile device is aimed at a scene including optical patterns.

While the auto-focus feature is often helpful for recreationalphotography, the auto-focus feature can slow down scanning (e.g.,detecting and/or decoding) optical patterns. For example, scanningoptical patterns can be interrupted during the focus algorithm of thecamera and/or tracking of optical patterns can be lost. Furthermore,scanning speed is often more important than image quality for detectionand decoding processes. For example, an image slightly out of focusmight be considered unacceptable for recreational photography butacceptable for scanning optical patterns. To that end, a system 900 maydisable an AF feature of the camera and/or one or more focus strategiesbelow may be implemented.

A real scene may include multiple optical patterns 914, as in the retailshelving environment described in reference to FIG. 2 . In anillustrative example, the system 900 is a tablet or a smartphoneincorporating a camera that is controlled by software stored in memoryof the system 900. In some cases, as when the depth of field of thecamera is limited, an AF feature of the system 900 may set the focusposition of the camera such that optical patterns 914 at eye-level arein focus, while those optical patterns 914 on lower shelves are out offocus. In this way, images captured by the camera include opticalpatterns 914 that can be decoded on the top shelf, are detected on themiddle shelf, and are undetected on the lower shelf. For those opticalpatterns 914 appearing in focus, the system 900 may generate and/orpresent graphical elements 922 overlaid on the optical patterns 914. Incontrast, a first optical pattern 914-1 on the middle shelf, detectedbut not decoded, may be identified by a first graphical element 922-1,indicating that the first optical pattern 914-1 is detected, but is outof focus and cannot be decoded by the system 900.

In some embodiments, the system 900 may implement manual or automaticfocus control strategies to capture an image of the real scene in whichthe first optical pattern 914-1 is in focus (operation 950). Forexample, the system 900 may receive a user action 912 that triggers asingle focus cycle. The user action 912 may be a user interaction with adisplay 910 of the system (e.g., a screen tap), and may cause the system900 to focus on features in a region of the image corresponding with theuser action 912. For example, a screen tap on the display 910 in theregion of the first optical pattern 914-1 may cause the system 900 tofocus on the first optical pattern 914-1, rather than on those opticalpatterns 914 appearing on the top shelf nearer the system 900.

The focus strategy can be implemented on an application level (e.g.,instead of a driver level). In some embodiments, a plurality of cameratypes (e.g., different makes, models, software versions, etc.) aretested and a focus strategy for each camera type is selected. Thusdifferent focus strategies can be used for different devices (e.g., byevaluating focus strategies under different conditions and selecting onethat performs best, or to a threshold criteria, depending on the devicea scanning application runs on). In some embodiments, the system 900references a list of allowed devices, determines that the auto-focusfeature is not disabled, and disables the auto-focus if the device isnot on the list of allowed devices. In this way, the system 900 mayexecute a scanning application (e.g., where the scanning applicationruns on a mobile device and is used to detect and/or decode opticalpatterns) may check a model of a mobile device running the scanningapplication, and may select a focus strategy (and/or other strategydisclosed herein) based on the model of device. The focus strategy mayinclude disabling an AF feature of a camera of the mobile device and/ordisabling image enhancement features of the camera (e.g., motioncompensation features or face-recognition adaptive metering, etc.).

In some embodiments, the system 900 may employ a focus strategy thatincludes a fixed focal position of the camera. For example, a mobiledevice is set at a known height from a table. Documents with the opticalpatterns are placed on the table. After the scanning applicationinitializes, the focus is set to a predetermined (e.g., a saved) focus,which can improve scanning small optical patterns by reducing the numberof repeated focus cycles. By using a fixed focus, the camera does nottry to refocus as documents are removed and/or added to the table. Inanother implementation, a fixed focal position can be used to scan codeson sides of objects on a conveyer belt; as there is a gap betweenobjects on the conveyer belt, the fixed focus can keep the camera fromtrying to refocus at a far distance during periods between objects. Thecamera focal position can be set (e.g., fixed) manually, by software, orby a user triggering a focus algorithm manually (e.g., with continuousauto-focus disabled).

FIG. 10 depicts an example block flow diagram describing manual focuscontrol to facilitate decoding of a pattern in an image of a real scene,in accordance with some embodiments. For example, the AF feature can bedisabled at operation 1005. Disabling the AF feature permits a system1000 implementing the operations to reduce redundant focus cycles andreduces the likelihood that the camera will focus on a feature otherthan an optical pattern. The focus algorithm can be triggered manuallyat operation 1010 by receiving a user action 1012. In some embodiments,the system 1000 does not implement the focus algorithm until there is atap on a screen of the mobile device (e.g., user action 912 of FIG. 9 ).

After receiving the user action, the system triggers a focus cycle 1017at operation 1015. The focus cycle 1017 may include, but is not limitedto, a single iteration of an AF feature of the system 1000, a focusalgorithm tuned to focus on optical patterns, or an increment betweenfixed focal positions with accompanying graphical elements indicating ifthe detected optical pattern is decoded. In this way, the opticalpatterns in the camera of the system 1000 may be focused onto theoptical patterns, and the optical patterns may be decoded at operation1020. The process of triggering focus cycles may be repeated for a realscene including multiple optical patterns at different locations. Forexample, the system 1000 may receive a second user action 1012 atoperation 1025, and in response may trigger the focus cycle 1017 atoperation 1030 to focus on a different optical pattern at a differentfocal position. In some embodiments, the user action 1012 is combinedwith instructions to the user. For example, a store employee could scanbarcodes at one shelf and then be instructed to tap a button to move toa new row of shelves. After the store employee taps the button to moveto another row, the focus cycle 1017 is triggered and the camerarefocuses.

FIG. 11 depicts an example block flow diagram describing an automaticfocus control algorithm 1100 to facilitate decoding of a pattern in animage of a real scene, in accordance with some embodiments. The focusalgorithm of a camera can be triggered (e.g., automatically) if anoptical pattern is detected, but is out of focus in an image of the realscene to be used in decoding the optical patterns. Thus the mobiledevice can be used to scan multiple optical patterns quickly withoutfocus being triggered until an optical pattern cannot be decoded. Asopposed to typical AF features where the trigger includes an evaluationof whether an object or person in the real scene is in focus, asdetermined by the AF algorithm, the system may trigger a focus cyclewithout explicitly focusing on an optical pattern. In an illustrativeexample, a mobile device including a camera runs a scanning applicationimplementing the automatic focus control algorithm 1100, a user of themobile device points the camera toward a group of barcodes on twostorage shelves. The mobile device detects and decodes a first sub-groupof barcodes on a first shelf, and triggers a focus cycle to decode asecond sub-group of barcodes on a second shelf.

In another illustrative example, the system can trigger a focus cycle ofa camera after detecting on a scene change. For example, the system mayascertain a motion estimation value (MEV), and may trigger a focus cycleif the MEV exceeds a threshold value. Similarly, motion data from aninertial measurement unit or gyroscope included in the system can beused (e.g., by itself or in combination with a visual technique). TheMEV can be calculated by identifying edges and calculating how manyedges there are in an image and/or how strong the edges are. In someembodiments, a full image intensity plane or a cropped area fromintensity of an image plane is used to calculate the MEV. In someembodiments, when the MEV is above a first threshold, it means thatthere is a big movement in a camera's field of view. When the MEV dropsbelow a second threshold and remains below the second threshold for apredetermined amount of time (e.g., for less than 1 second, 1, 2, 3, 4,5, 6, or 10 seconds, or more) and/or frames (e.g., for 20, 30, or 60frames), the system can determine that the camera is stabilized on a newscene, and the focus algorithm is triggered. The second threshold can bethe same as the first threshold. When the MEV is above the firstthreshold, the system stops scanning for codes until the MEV is belowthe second threshold. In some embodiments, a brightness value isrecorded and as the brightness value changes beyond a threshold value,then the focus algorithm is triggered.

An embodiment of a process for calculating MEV comprises: detectingedges (e.g., using a convolution filter); identifying high contrastareas (e.g., more high contrast areas produce a lower MEV because highercontrast areas can mean less motion blur); and/or comparing aconvolution value frame to frame (higher differences frame to frameincrease the MEV). As MEV drops, the focus algorithm is triggered. Insome embodiments, homography is used to calculate a scene change (e.g.,movement from one row to another row).

In some configurations, a barcode is detected and the scanningapplication triggers the focus algorithm to focus on the barcode (e.g.,if the barcode could not be decoded). For example, a barcode is detectedin a plurality of images, and a spatial area of the images where thebarcode is detected is used for determining the focus. Some cameras havea mode to focus on faces as a priority. If so, face-priority focus couldbe deactivated and a barcode priority could be used for focus processes.

As illustrated in FIG. 11 , an example automatic focus strategy includesdisabling an AF feature of a camera at operation 1105. The systemimplementing the automatic focus strategy may disable the AF featurebefore scanning for optical patterns in an image of a real sceneacquired by the camera at operation 1110. Scanning for optical patternsmay include, but is not limited to, detecting optical patterns,recognizing optical patterns, decoding optical patterns, or generatingand/or presenting graphical elements as described in more detail inreference to FIGS. 1-2 , above. When one or more optical patterns aredetected that cannot be decoded, the system may trigger a focus cycle,which may or may not be centered on an optical pattern that was notdecoded at operation 1115. As described previously, the system may beunable to decode an optical pattern for more than one reason, such asthat the optical pattern is overexposed or is too small in the image. Toascertain whether the codes are in focus at operation 1120, the systemmay compare a focus measurement of detected optical patterns against athreshold, and if focus is sufficient, the system decodes the opticalpattern at operation 1125. In some embodiments, the system may implementoperation 1120 by attempting to decode the optical patterns in the imageof the real scene without additional evaluation (e.g., by ascertaining aresolution of the optical patterns). Where the optical patterns remainout of focus after the focus cycle, the system may trigger one or moreadditional focus cycles at operation 1135, until every optical patternin the camera's FOV is decoded. In some embodiments, the system mayreactivate the AF feature of the camera after all the optical patternsare successfully decoded.

D. Multi-Threading

FIG. 12 depicts an example block flow diagram describing multi-coreprocessor threading to facilitate decoding of a pattern in an image of areal scene, in accordance with some embodiments.

Some mobile device have CPUs with different core types (e.g., abig.LITTLE architecture), where a subset of the cores are optimized forhigh performance, others for low power consumption. Depending on whichcore code gets executed by, execution may be significantly slower (up to2× slower). Scheduling is done by the operating system and as such,scheduling decisions may follow criteria based on system priorities,rather than application priorities. By providing direction or hints tothe operating system on which cores certain code is to be executed,runtime performance of a scanning application can be optimized.

FIG. 12 depicts an example block flow diagram describing multi-coreprocessor threading to facilitate decoding of a pattern in an image of areal scene, in accordance with some embodiments. In an illustrativeembodiment, the system 1200 is a mobile device having a multi-coreprocessor 1250. The multi-core processor 1250 includes a coreconfiguration of low power cores 1255, and high performance cores 1260.In a default configuration, without restrictions, operations of ascanning application can be executed on either low power cores 1255 orhigh performance cores 1260, sometimes switching between cores. Thesystem 1200 may restrict processing to the high performance cores 1260,such that detection, decoding, and performance improvement strategies(e.g., exposure, zoom, focus, etc.) can be improved in terms ofexecution time.

In an embodiment of a method for multi-threading, the system 1200detects hardware information describing the multi-core processor 1250 atoperation 1205. The system 1200 looks up identifiers for the low powercores 1255 and the high performance cores 1260, at operation 1210, toidentify the cores of the multi-core processor 1250. Based on the coreinformation, the system 1200 enables the scanning application to executeon only the performance cores 1260. The system 1200 scans the opticalpatterns at operation 1220, until all the optical patterns included areprocessed (e.g., detected and/or decoded), after which, the low powercores 1255 are enabled at operation 1225.

In an illustrative example where the system 1200 is a mobile phone, thesystem 1200 may determine a phone model to identify those cores of thephone processor that are high speed cores, and prevents the scanningapplication from executing operations on other cores while datacapturing processes are running. After data capture finishes, therestriction on using other cores is removed. Such an approach permitsthe system 1200 to process and capture data encoded in optical patternsmore rapidly, with less latency, and further permits the parallelizationof operations without operations being shifted to low power cores 1255,which improves the speed of the scanning application.

In some embodiments, a mobile device is used for decoding an opticalpattern in a real scene. A mobile device may include a display, acamera, one or more processors in communication with the camera and withthe display, and one or more memory devices storing instructions. Theinstructions, when executed by the one or more processors, may cause themobile device to detect a hardware configuration of the one or moreprocessors. The instructions, when executed by the one or moreprocessors, may cause the mobile device to identify a first core of theone or more processors, the first core being a high performance core.The instructions, when executed by the one or more processors, may causethe mobile device to identify a second core of the one or moreprocessors, the second core being a low power core. The instructions,when executed by the one or more processors, may also cause the mobiledevice to execute, using the first core of the one or more processors,further instructions that, when executed by the first core, may causethe one or more processors to detect a plurality of optical patterns ina scene, the optical patterns encoding a plurality of objectidentifiers. The further instructions, when executed by the first core,may cause the one or more processors to acquire one or more images ofthe scene using the camera, the one or more images including theplurality of optical patterns. The further instructions, when executedby the first core, may also cause the one or more processors to decodethe plurality of optical patterns in the one or more images of thescene, generating the plurality of object identifiers.

In some embodiments, the optical pattern may be or include a barcodeconstructed of parallel bars. The instructions, when executed by the oneor more processors, may further cause the one or more processors todisable the second core after identifying the second core and beforedetecting the plurality of optical patterns in the scene and enable thesecond core after decoding the plurality of optical patterns. Theinstructions, when executed by the one or more processors, may furthercause the one or more processors to identify a third core of the one ormore processors, the third core being a high performance core. Thefurther instructions may be executed by the first core and the thirdcore, but not executed by the second core.

E. System Architecture

FIG. 13 is a simplified block diagram of a computing device 1300.Computing device 1300 can implement some or all functions, behaviors,and/or capabilities described above that would use electronic storage orprocessing, as well as other functions, behaviors, or capabilities notexpressly described. Computing device 1300 includes a processingsubsystem 1302, a storage subsystem 1304, a user interface 1306, and/ora communication interface 1308. Computing device 1300 can also includeother components (not explicitly shown) such as a battery, powercontrollers, and other components operable to provide various enhancedcapabilities. In various embodiments, computing device 1300 can beimplemented in a desktop or laptop computer, mobile device (e.g., tabletcomputer, smart phone, mobile phone), wearable device, media device,application specific integrated circuits (ASICs), digital signalprocessors (DSPs), digital signal processing devices (DSPDs),programmable logic devices (PLDs), field programmable gate arrays(FPGAs), processors, controllers, micro-controllers, microprocessors, orelectronic units designed to perform a function or combination offunctions described above.

Storage subsystem 1304 can be implemented using a local storage and/orremovable storage medium, e.g., using disk, flash memory (e.g., securedigital card, universal serial bus flash drive), or other nontransitorystorage medium, or a combination of media, and can include volatileand/or nonvolatile storage media. Local storage can include randomaccess memory (RAM), including dynamic RAM (DRAM), static RAM (SRAM), orbattery backed up RAM. In some embodiments, storage subsystem 1304 canstore one or more applications and/or operating system programs to beexecuted by processing subsystem 1302, including programs to implementsome or all operations described above that would be performed using acomputer. For example, storage subsystem 1304 can store one or more codemodules 1310 for implementing one or more method steps described above.

A firmware and/or software implementation may be implemented withmodules (e.g., procedures, functions, and so on). A machine-readablemedium tangibly embodying instructions may be used in implementingmethodologies described herein. Code modules 1310 (e.g., instructionsstored in memory) may be implemented within a processor or external tothe processor. As used herein, the term “memory” refers to a type oflong term, short term, volatile, nonvolatile, or other storage mediumand is not to be limited to particular types of memory or number ofmemories or type of media upon which memory is stored.

Moreover, the term “storage medium” or “storage device” may representone or more memories for storing data, including read only memory (ROM),RAM, magnetic RAM, core memory, magnetic disk storage mediums, opticalstorage mediums, flash memory devices and/or other machine readablemediums for storing information. The term “machine-readable medium”includes, but is not limited to, portable or fixed storage devices,optical storage devices, wireless channels, and/or various other storagemediums capable of storing instruction(s) and/or data.

Furthermore, embodiments may be implemented by hardware, software,scripting languages, firmware, middleware, microcode, hardwaredescription languages, and/or combinations thereof. When implemented insoftware, firmware, middleware, scripting language, and/or microcode,program code or code segments to perform tasks may be stored in amachine readable medium such as a storage medium. A code segment (e.g.,code module 1310) or machine-executable instruction may represent aprocedure, a function, a subprogram, a program, a routine, a subroutine,a module, a software package, a script, a class, or a combination ofinstructions, data structures, and/or program statements. A code segmentmay be coupled to another code segment or a hardware circuit by passingand/or receiving information, data, arguments, parameters, and/or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted by suitable means including memory sharing,message passing, token passing, network transmission, etc.

Implementation of the techniques, blocks, steps and means describedabove may be done in various ways. For example, these techniques,blocks, steps and means may be implemented in hardware, software, or acombination thereof. For a hardware implementation, the processing unitsmay be implemented within one or more ASICs, DSPs, DSPDs, PLDs, FPGAs,processors, controllers, micro-controllers, microprocessors, otherelectronic units designed to perform the functions described above,and/or a combination thereof.

Each code module 1310 may comprise sets of instructions (codes) embodiedon a computer-readable medium that directs a processor of a computingdevice 1300 to perform corresponding actions. The instructions may beconfigured to run in sequential order, in parallel (such as underdifferent processing threads), or in a combination thereof. Afterloading a code module 1310 on a general purpose computer system, thegeneral purpose computer is transformed into a special purpose computersystem.

Computer programs incorporating various features described herein (e.g.,in one or more code modules 1310) may be encoded and stored on variouscomputer readable storage media. Computer-readable media encoded withthe program code may be packaged with a compatible electronic device, orthe program code may be provided separately from electronic devices(e.g., via Internet download or as a separately packagedcomputerreadable storage medium). Storage subsystem 1304 can also storeinformation useful for establishing network connections using thecommunication interface 1308.

User interface 1306 can include input devices (e.g., touch pad, touchscreen, scroll wheel, click wheel, dial, button, switch, keypad,microphone, etc.), as well as output devices (e.g., video screen,indicator lights, speakers, headphone jacks, virtual- oraugmented-reality display, etc.), together with supporting electronics(e.g., digitaltoanalog or analogtodigital converters, signal processors,etc.). A user can operate input devices of user interface 1306 to invokethe functionality of computing device 1300 and can view and/or hearoutput from computing device 1300 via output devices of user interface1306. For some embodiments, the user interface 1306 might not be present(e.g., for a process using an ASIC).

Processing subsystem 1302 can be implemented as one or more processors(e.g., integrated circuits, one or more singlecore or multicoremicroprocessors, microcontrollers, central processing unit, graphicsprocessing unit, etc.). In operation, processing subsystem 1302 cancontrol the operation of computing device 1300. In some embodiments,processing subsystem 1302 can execute a variety of programs in responseto program code and can maintain multiple concurrently executingprograms or processes. At a given time, some or all of a program code tobe executed can reside in processing subsystem 1302 and/or in storagemedia, such as storage subsystem 1304. Through programming, processingsubsystem 1302 can provide various functionality for computing device1300. Processing subsystem 1302 can also execute other programs tocontrol other functions of computing device 1300, including programsthat may be stored in storage subsystem 1304.

Communication interface 1308 can provide voice and/or data communicationcapability for computing device 1300. In some embodiments, communicationinterface 1308 can include radio frequency (RF) transceiver componentsfor accessing wireless data networks (e.g., Wi-Fi network; 3G, 4G/LTE;etc.), mobile communication technologies, components for shortrangewireless communication (e.g., using Bluetooth communication standards,NFC, etc.), other components, or combinations of technologies. In someembodiments, communication interface 1308 can provide wired connectivity(e.g., universal serial bus, Ethernet, universal asynchronousreceiver/transmitter, etc.) in addition to, or in lieu of, a wirelessinterface. Communication interface 1308 can be implemented using acombination of hardware (e.g., driver circuits, antennas,modulators/demodulators, encoders/decoders, and other analog and/ordigital signal processing circuits) and software components. In someembodiments, communication interface 1308 can support multiplecommunication channels concurrently. In some embodiments thecommunication interface 1308 is not used.

It will be appreciated that computing device 1300 is illustrative andthat variations and modifications are possible. A computing device canhave various functionality not specifically described (e.g., voicecommunication via cellular telephone networks) and can includecomponents appropriate to such functionality.

Further, while the computing device 1300 is described with reference toparticular blocks, it is to be understood that these blocks are definedfor convenience of description and are not intended to imply aparticular physical arrangement of component parts. For example, theprocessing subsystem 1302, the storage subsystem, the user interface1306, and/or the communication interface 1308 can be in one device ordistributed among multiple devices.

Further, the blocks need not correspond to physically distinctcomponents. Blocks can be configured to perform various operations,e.g., by programming a processor or providing appropriate controlcircuitry, and various blocks might or might not be reconfigurabledepending on how an initial configuration is obtained. Embodiments ofthe present invention can be realized in a variety of apparatusincluding electronic devices implemented using a combination ofcircuitry and software. Electronic devices described herein can beimplemented using computing device 1300.

Various features described herein, e.g., methods, apparatus, computerreadable media and the like, can be realized using a combination ofdedicated components, programmable processors, and/or other programmabledevices. Processes described herein can be implemented on the sameprocessor or different processors. Where components are described asbeing configured to perform certain operations, such configuration canbe accomplished, e.g., by designing electronic circuits to perform theoperation, by programming programmable electronic circuits (such asmicroprocessors) to perform the operation, or a combination thereof.Further, while the embodiments described above may make reference tospecific hardware and software components, those skilled in the art willappreciate that different combinations of hardware and/or softwarecomponents may also be used and that particular operations described asbeing implemented in hardware might be implemented in software or viceversa.

Specific details are given in the above description to provide anunderstanding of the embodiments. However, it is understood that theembodiments may be practiced without these specific details. In someinstances, well-known circuits, processes, algorithms, structures, andtechniques may be shown without unnecessary detail in order to avoidobscuring the embodiments.

While the principles of the disclosure have been described above inconnection with specific apparatus and methods, it is to be understoodthat this description is made only by way of example and not aslimitation on the scope of the disclosure. Embodiments were chosen anddescribed in order to explain the principles of the invention andpractical applications to enable others skilled in the art to utilizethe invention in various embodiments and with various modifications, asare suited to a particular use contemplated. It will be appreciated thatthe description is intended to cover modifications and equivalents.

Also, it is noted that the embodiments may be described as a processwhich is depicted as a flowchart, a flow diagram, a data flow diagram, astructure diagram, or a block diagram. Although a flowchart may describethe operations as a sequential process, many of the operations can beperformed in parallel or concurrently. In addition, the order of theoperations may be re-arranged. A process is terminated when itsoperations are completed, but could have additional steps not includedin the figure. A process may correspond to a method, a function, aprocedure, a subroutine, a subprogram, etc.

A recitation of “a”, “an”, or “the” is intended to mean “one or more”unless specifically indicated to the contrary. Patents, patentapplications, publications, and descriptions mentioned here areincorporated by reference in their entirety for all purposes. None isadmitted to be prior art.

What is claimed is:
 1. A system for decoding optical patterns in anenvironment, the system comprising: a camera; one or more processors;and one or more memory devices storing instructions that, when executed,cause the one or more processors to: acquire a first image of a sceneusing the camera, wherein a magnification of the camera is set at afirst magnification; detect an optical pattern in the first image, theoptical pattern encoding an object identifier; ascertain that aresolution of the first image is not sufficient to decode the opticalpattern; increase the magnification of the camera from the firstmagnification to a second magnification, after ascertaining that theresolution of the first image is not sufficient to decode the opticalpattern, wherein the magnification of the camera is increased by apredetermined magnification factor; acquire a second image using thesecond magnification; and decode the optical pattern, after acquiringthe second image, obtaining the object identifier.
 2. The system ofclaim 1, wherein the camera is part of a smartphone.
 3. The system ofclaim 1, wherein the one or more processors are configured to: ascertainthat the magnification of the camera has reached a limit; and provide auser prompt that the magnification of the camera has reached the limit.4. The system of claim 3, wherein the user prompt is an auditory prompt.5. A method for decoding optical patterns in an environment, the methodcomprising: acquiring a first image of a scene using a camera, wherein amagnification of the camera is set at a first magnification; detectingan optical pattern in the first image, the optical pattern encoding anobject identifier; ascertaining that a resolution of the first image isnot sufficient to decode the optical pattern; increasing themagnification of the camera from the first magnification to a secondmagnification, after ascertaining that the resolution of the first imageis not sufficient to decode the optical pattern, wherein themagnification of the camera is increased by a predeterminedmagnification factor; acquiring a second image using the secondmagnification; and decoding the optical pattern, after acquiring thesecond image, obtaining the object identifier.
 6. The method of claim 5,the method further comprising: ascertaining a bit depth of the camera;and increasing the magnification of the camera based on the bit depth ofthe camera.
 7. The method of claim 5, wherein: increasing themagnification is performed automatically after a waiting period; and thewaiting period is equal to or greater than one second.
 8. The method ofclaim 5, the method further comprising automatically returning to thefirst magnification after the optical pattern is decoded.
 9. The methodof claim 5, wherein the magnification of the camera is increasedautomatically, and increasing the magnification is accompanied by avisual or auditory indication.
 10. The method of claim 5, furthercomprising automatically increasing the magnification of the camerathrough multiple, predetermined increments.
 11. The method of claim 5,further comprising tracking the optical pattern in a plurality of imagesbefore acquiring the first image of the scene using the camera.
 12. Themethod of claim 5, further comprising: receiving a user action; andincreasing the magnification of the camera from the first magnificationto the second magnification based on receiving the user action.
 13. Amethod for decoding optical patterns in an environment, the methodcomprising: acquiring a first image of a scene using a camera, wherein:a magnification of the camera is set at a first magnification; and thefirst image comprises an optical pattern encoding an object identifier;receiving a user action; increasing magnification of the camera from thefirst magnification to a second magnification, based on the user action,wherein the magnification of the camera is increased by a predeterminedmagnification factor; acquiring a second image using the secondmagnification; and decoding the optical pattern in the second image,obtaining the object identifier.
 14. The method of claim 13, wherein:the user action is a first user action; and the method furthercomprises: receiving a second user action; and returning themagnification of the camera to the first magnification, based on theuser action.
 15. The method of claim 13, wherein: the user action is afirst user action; the predetermined magnification factor is a firstpredetermined magnification factor; and the method further comprises:receiving a second user action; and increasing the magnification of thecamera from the second magnification to a third magnification, based onthe second user action, wherein the magnification of the camera isincreased by a second predetermined magnification factor going from thesecond magnification to the third magnification.
 16. The method of claim13, wherein the user action is a tap on a display.
 17. The method ofclaim 13, further comprising: detecting the optical pattern in the firstimage; and ascertaining that a resolution of the first image is notsufficient to decode the optical pattern.
 18. The method of claim 13,wherein the predetermined magnification factor is equal to or greaterthan 1.5 and equal to or less than
 3. 19. The method of claim 13,wherein there are only two magnification levels used during decodingoptical patterns, the first magnification and the second magnification.20. The method of claim 13, wherein: the magnification of the camera islimited to a set of magnifications; the set of magnifications includesthe first magnification and the second magnification; and eachmagnification in the set of magnifications is separated by an incrementof at least 0.5× compared to a preceding magnification.